De-sequencing encoded data slices

ABSTRACT

A method begins by a processing module obtaining at least an ordering threshold number of encoded data slices to produce obtained encoded data slices. The method continues with the processing module ordering the obtained encoded data slices based on a pseudo-random de-sequencing order to produce a plurality of sets of encoded data slices. The method continues with the processing module dispersed storage error decoding the plurality of sets of encoded data slices to produce a plurality of encrypted data segments. The method continues with the processing module decrypting the plurality of encrypted data segments to produce a plurality of data segments. The method continues with the processing module aggregating the plurality of data segments to produce a data stream.

CROSS REFERENCE TO RELATED PATENTS

The present U.S. Utility Patent Application claims priority pursuant to35 U.S.C. §119(e) to U.S. Provisional Application Ser. No. 61/299,245,entitled “Secure Data Transmission Utilizing Distributed Storage,” filedJan. 28, 2010, pending, which is hereby incorporated herein by referencein its entirety and made part of the present U.S. Utility PatentApplication for all purposes.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not applicable

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC

Not applicable

BACKGROUND OF THE INVENTION

1. Technical Field of the Invention

This invention relates generally to computing systems and moreparticularly to data storage solutions within such computing systems.

2. Description of Related Art

Computers are known to communicate, process, and store data. Suchcomputers range from wireless smart phones to data centers that supportmillions of web searches, stock trades, or on-line purchases every day.In general, a computing system generates data and/or manipulates datafrom one form into another. For instance, an image sensor of thecomputing system generates raw picture data and, using an imagecompression program (e.g., JPEG, MPEG, etc.), the computing systemmanipulates the raw picture data into a standardized compressed image.

With continued advances in processing speed and communication speed,computers are capable of processing real time multimedia data forapplications ranging from simple voice communications to streaming highdefinition video. As such, general-purpose information appliances arereplacing purpose-built communications devices (e.g., a telephone). Forexample, smart phones can support telephony communications but they arealso capable of text messaging and accessing the internet to performfunctions including email, web browsing, remote applications access, andmedia communications (e.g., telephony voice, image transfer, musicfiles, video files, real time video streaming. etc.).

Each type of computer is constructed and operates in accordance with oneor more communication, processing, and storage standards. As a result ofstandardization and with advances in technology, more and moreinformation content is being converted into digital formats. Forexample, more digital cameras are now being sold than film cameras, thusproducing more digital pictures. As another example, web-basedprogramming is becoming an alternative to over the air televisionbroadcasts and/or cable broadcasts. As further examples, papers, books,video entertainment, home video, etc. are now being stored digitally,which increases the demand on the storage function of computers.

A typical computer storage system includes one or more memory devicesaligned with the needs of the various operational aspects of thecomputer's processing and communication functions. Generally, theimmediacy of access dictates what type of memory device is used. Forexample, random access memory (RAM) memory can be accessed in any randomorder with a constant response time, thus it is typically used for cachememory and main memory. By contrast, memory device technologies thatrequire physical movement such as magnetic disks, tapes, and opticaldiscs, have a variable response time as the physical movement can takelonger than the data transfer, thus they are typically used forsecondary memory (e.g., hard drive, backup memory, etc.).

A computer's storage system will be compliant with one or more computerstorage standards that include, but are not limited to, network filesystem (NFS), flash file system (FFS), disk file system (DFS), smallcomputer system interface (SCSI), internet small computer systeminterface (iSCSI), file transfer protocol (FTP), and web-baseddistributed authoring and versioning (WebDAV). These standards specifythe data storage format (e.g., files, data objects, data blocks,directories, etc.) and interfacing between the computer's processingfunction and its storage system, which is a primary function of thecomputer's memory controller.

Despite the standardization of the computer and its storage system,memory devices fail; especially commercial grade memory devices thatutilize technologies incorporating physical movement (e.g., a discdrive). For example, it is fairly common for a disc drive to routinelysuffer from bit level corruption and to completely fail after threeyears of use. One solution is to a higher-grade disc drive, which addssignificant cost to a computer.

Another solution is to utilize multiple levels of redundant disc drivesto replicate the data into two or more copies. One such redundant driveapproach is called redundant array of independent discs (RAID). In aRAID device, a RAID controller adds parity data to the original databefore storing it across the array. The parity data is calculated fromthe original data such that the failure of a disc will not result in theloss of the original data. For example, RAID 5 uses three discs toprotect data from the failure of a single disc. The parity data, andassociated redundancy overhead data, reduces the storage capacity ofthree independent discs by one third (e.g., n−1=capacity). RAID 6 canrecover from a loss of two discs and requires a minimum of four discswith a storage capacity of n−2.

While RAID addresses the memory device failure issue, it is not withoutits own failures issues that affect its effectiveness, efficiency andsecurity. For instance, as more discs are added to the array, theprobability of a disc failure increases, which increases the demand formaintenance. For example, when a disc fails, it needs to be manuallyreplaced before another disc fails and the data stored in the RAIDdevice is lost. To reduce the risk of data loss, data on a RAID deviceis typically copied on to one or more other RAID devices. While thisaddresses the loss of data issue, it raises a security issue sincemultiple copies of data are available, which increases the chances ofunauthorized access. Further, as the amount of data being stored grows,the overhead of RAID devices becomes a non-trivial efficiency issue.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a computingsystem in accordance with the invention;

FIG. 2 is a schematic block diagram of an embodiment of a computing corein accordance with the invention;

FIG. 3 is a schematic block diagram of an embodiment of a distributedstorage processing unit in accordance with the invention;

FIG. 4 is a schematic block diagram of an embodiment of a grid module inaccordance with the invention;

FIG. 5 is a diagram of an example embodiment of error coded data slicecreation in accordance with the invention;

FIG. 6 is another schematic block diagram of another embodiment of acomputing system in accordance with the invention;

FIG. 7 is another schematic block diagram of an embodiment of adispersed storage (DS) processing module in accordance with theinvention;

FIG. 8A is a schematic block diagram of an embodiment of a storagemodule in accordance with the invention;

FIGS. 8B-8E are diagrams illustrating examples of sequencing andselecting encoded data slices in accordance with the invention;

FIG. 9 is a flowchart illustrating an example of encoding data toproduce encoded data slices in accordance with the invention;

FIG. 10 is a flowchart illustrating an example of decoding encoded dataslices to produce data in accordance with the invention;

FIG. 11 is a flowchart illustrating another example of encoding data toproduce encoded data slices in accordance with the invention;

FIG. 12 is a flowchart illustrating another example of decoding encodeddata slices to produce data in accordance with the invention;

FIG. 13 is a flowchart illustrating another example of encoding data toproduce encoded data slices in accordance with the invention;

FIG. 14 is a flowchart illustrating another example of decoding encodeddata slices to produce data in accordance with the invention;

FIG. 15 is a flowchart illustrating another example of encoding data toproduce encoded data slices in accordance with the invention;

FIG. 16 is a flowchart illustrating another example of decoding encodeddata slices to produce data in accordance with the invention;

FIG. 17 is a flowchart illustrating another example of encoding data toproduce encoded data slices in accordance with the invention;

FIG. 18 is a flowchart illustrating another example of decoding encodeddata slices to produce data in accordance with the invention;

FIG. 19 is a flowchart illustrating another example of encoding data toproduce encoded data slices in accordance with the invention;

FIG. 20 is a flowchart illustrating another example of decoding encodeddata slices to produce data in accordance with the invention;

FIG. 21 is a flowchart illustrating another example of encoding data toproduce encoded data slices in accordance with the invention;

FIG. 22 is a flowchart illustrating another example of decoding encodeddata slices to produce data in accordance with the invention;

FIG. 23 is a flowchart illustrating another example of encoding data toproduce encoded data slices in accordance with the invention;

FIG. 24 is a flowchart illustrating another example of decoding encodeddata slices to produce data in accordance with the invention;

FIG. 25 is a flowchart illustrating another example of encoding data toproduce encoded data slices in accordance with the invention; and

FIG. 26 is a flowchart illustrating another example of decoding encodeddata slices to produce data in accordance with the invention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of a computing system 10 thatincludes one or more of a first type of user devices 12, one or more ofa second type of user devices 14, at least one distributed storage (DS)processing unit 16, at least one DS managing unit 18, at least onestorage integrity processing unit 20, and a distributed storage network(DSN) memory 22 coupled via a network 24. The network 24 may include oneor more wireless and/or wire lined communication systems; one or moreprivate intranet systems and/or public internet systems; and/or one ormore local area networks (LAN) and/or wide area networks (WAN).

The DSN memory 22 includes a plurality of distributed storage (DS) units36 for storing data of the system. Each of the DS units 36 includes aprocessing module and memory and may be located at a geographicallydifferent site than the other DS units (e.g., one in Chicago, one inMilwaukee, etc.). The processing module may be a single processingdevice or a plurality of processing devices. Such a processing devicemay be a microprocessor, micro-controller, digital signal processor,microcomputer, central processing unit, field programmable gate array,programmable logic device, state machine, logic circuitry, analogcircuitry, digital circuitry, and/or any device that manipulates signals(analog and/or digital) based on hard coding of the circuitry and/oroperational instructions.

The processing module may have an associated memory and/or memoryelement, which may be a single memory device, a plurality of memorydevices, and/or embedded circuitry of the processing module. Such amemory device may be a read-only memory, random access memory, volatilememory, non-volatile memory, static memory, dynamic memory, flashmemory, cache memory, and/or any device that stores digital information.Note that if the processing module includes more than one processingdevice, the processing devices may be centrally located (e.g., directlycoupled together via a wired and/or wireless bus structure) or may bedistributedly located (e.g., cloud computing via indirect coupling via alocal area network and/or a wide area network). Further note that whenthe processing module implements one or more of its functions via astate machine, analog circuitry, digital circuitry, and/or logiccircuitry, the memory and/or memory element storing the correspondingoperational instructions may be embedded within, or external to, thecircuitry comprising the state machine, analog circuitry, digitalcircuitry, and/or logic circuitry. Still further note that, the memoryelement stores, and the processing module executes, hard coded and/oroperational instructions corresponding to at least some of the stepsand/or functions illustrated in FIGS. 1-26.

Each of the user devices 12-14, the DS processing unit 16, the DSmanaging unit 18, and the storage integrity processing unit 20 may be aportable computing device (e.g., a social networking device, a gamingdevice, a cell phone, a smart phone, a personal digital assistant, adigital music player, a digital video player, a laptop computer, ahandheld computer, a video game controller, and/or any other portabledevice that includes a computing core) and/or a fixed computing device(e.g., a personal computer, a computer server, a cable set-top box, asatellite receiver, a television set, a printer, a fax machine, homeentertainment equipment, a video game console, and/or any type of homeor office computing equipment). Such a portable or fixed computingdevice includes a computing core 26 and one or more interfaces 30, 32,and/or 33. An embodiment of the computing core 26 will be described withreference to FIG. 2.

With respect to the interfaces, each of the interfaces 30, 32, and 33includes software and/or hardware to support one or more communicationlinks via the network 24 and/or directly. For example, interfaces 30support a communication link (wired, wireless, direct, via a LAN, viathe network 24, etc.) between the first type of user device 14 and theDS processing unit 16. As another example, DSN interface 32 supports aplurality of communication links via the network 24 between the DSNmemory 22 and the DS processing unit 16, the first type of user device12, and/or the storage integrity processing unit 20. As yet anotherexample, interface 33 supports a communication link between the DSmanaging unit 18 and any one of the other devices and/or units 12, 14,16, 20, and/or 22 via the network 24.

In general and with respect to data storage, the system 10 supportsthree primary functions: distributed network data storage management,distributed data storage and retrieval, and data storage integrityverification. In accordance with these three primary functions, data canbe distributedly stored in a plurality of physically different locationsand subsequently retrieved in a reliable and secure manner regardless offailures of individual storage devices, failures of network equipment,the duration of storage, the amount of data being stored, attempts athacking the data, etc.

The DS managing unit 18 performs distributed network data storagemanagement functions, which include establishing distributed datastorage parameters, performing network operations, performing networkadministration, and/or performing network maintenance. The DS managingunit 18 establishes the distributed data storage parameters (e.g.,allocation of virtual DSN memory space, distributed storage parameters,security parameters, billing information, user profile information,etc.) for one or more of the user devices 12-14 (e.g., established forindividual devices, established for a user group of devices, establishedfor public access by the user devices, etc.). For example, the DSmanaging unit 18 coordinates the creation of a vault (e.g., a virtualmemory block) within the DSN memory 22 for a user device (for a group ofdevices, or for public access). The DS managing unit 18 also determinesthe distributed data storage parameters for the vault. In particular,the DS managing unit 18 determines a number of slices (e.g., the numberthat a data segment of a data file and/or data block is partitioned intofor distributed storage) and a read threshold value (e.g., the minimumnumber of slices required to reconstruct the data segment).

As another example, the DS managing module 18 creates and stores,locally or within the DSN memory 22, user profile information. The userprofile information includes one or more of authentication information,permissions, and/or the security parameters. The security parameters mayinclude one or more of encryption/decryption scheme, one or moreencryption keys, key generation scheme, and data encoding/decodingscheme.

As yet another example, the DS managing unit 18 creates billinginformation for a particular user, user group, vault access, publicvault access, etc. For instance, the DS managing unit 18 tracks thenumber of times user accesses a private vault and/or public vaults,which can be used to generate a per-access bill. In another instance,the DS managing unit 18 tracks the amount of data stored and/orretrieved by a user device and/or a user group, which can be used togenerate a per-data-amount bill.

The DS managing unit 18 also performs network operations, networkadministration, and/or network maintenance. As at least part ofperforming the network operations and/or administration, the DS managingunit 18 monitors performance of the devices and/or units of the system10 for potential failures, determines the devices and/or unit'sactivation status, determines the devices' and/or units' loading, andany other system level operation that affects the performance level ofthe system 10. For example, the DS managing unit 18 receives andaggregates network management alarms, alerts, errors, statusinformation, performance information, and messages from the devices12-14 and/or the units 16, 20, 22. For example, the DS managing unit 18receives a simple network management protocol (SNMP) message regardingthe status of the DS processing unit 16.

The DS managing unit 18 performs the network maintenance by identifyingequipment within the system 10 that needs replacing, upgrading,repairing, and/or expanding. For example, the DS managing unit 18determines that the DSN memory 22 needs more DS units 36 or that one ormore of the DS units 36 needs updating.

The second primary function (i.e., distributed data storage andretrieval) begins and ends with a user device 12-14. For instance, if asecond type of user device 14 has a data file 38 and/or data block 40 tostore in the DSN memory 22, it send the data file 38 and/or data block40 to the DS processing unit 16 via its interface 30. As will bedescribed in greater detail with reference to FIG. 2, the interface 30functions to mimic a conventional operating system (OS) file systeminterface (e.g., network file system (NFS), flash file system (FFS),disk file system (DFS), file transfer protocol (FTP), web-baseddistributed authoring and versioning (WebDAV), etc.) and/or a blockmemory interface (e.g., small computer system interface (SCSI), internetsmall computer system interface (iSCSI), etc.). In addition, theinterface 30 may attach a user identification code (ID) to the data file38 and/or data block 40.

The DS processing unit 16 receives the data file 38 and/or data block 40via its interface 30 and performs a distributed storage (DS) process 34thereon (e.g., an error coding dispersal storage function). The DSprocessing 34 begins by partitioning the data file 38 and/or data block40 into one or more data segments, which is represented as Y datasegments. For example, the DS processing 34 may partition the data file38 and/or data block 40 into a fixed byte size segment (e.g., 2¹ to2^(n) bytes, where n=>2) or a variable byte size (e.g., change byte sizefrom segment to segment, or from groups of segments to groups ofsegments, etc.).

For each of the Y data segments, the DS processing 34 error encodes(e.g., forward error correction (FEC), information dispersal algorithm,or error correction coding) and slices (or slices then error encodes)the data segment into a plurality of error coded (EC) data slices 42-48,which is represented as X slices per data segment. The number of slices(X) per segment, which corresponds to a number of pillars n, is set inaccordance with the distributed data storage parameters and the errorcoding scheme. For example, if a Reed-Solomon (or other FEC scheme) isused in an n/k system, then a data segment is divided into n slices,where k number of slices is needed to reconstruct the original data(i.e., k is the threshold). As a few specific examples, the n/k factormay be 5/3; 6/4; 8/6; 8/5; 16/10.

For each slice 42-48, the DS processing unit 16 creates a unique slicename and appends it to the corresponding slice 42-48. The slice nameincludes universal DSN memory addressing routing information (e.g.,virtual memory addresses in the DSN memory 22) and user-specificinformation (e.g., user ID, file name, data block identifier, etc.).

The DS processing unit 16 transmits the plurality of EC slices 42-48 toa plurality of DS units 36 of the DSN memory 22 via the DSN interface 32and the network 24. The DSN interface 32 formats each of the slices fortransmission via the network 24. For example, the DSN interface 32 mayutilize an internet protocol (e.g., TCP/IP, etc.) to packetize theslices 42-48 for transmission via the network 24.

The number of DS units 36 receiving the slices 42-48 is dependent on thedistributed data storage parameters established by the DS managing unit18. For example, the DS managing unit 18 may indicate that each slice isto be stored in a different DS unit 36. As another example, the DSmanaging unit 18 may indicate that like slice numbers of different datasegments are to be stored in the same DS unit 36. For example, the firstslice of each of the data segments is to be stored in a first DS unit36, the second slice of each of the data segments is to be stored in asecond DS unit 36, etc. In this manner, the data is encoded anddistributedly stored at physically diverse locations to improved datastorage integrity and security. Further examples of encoding the datasegments will be provided with reference to one or more of FIGS. 2-26.

Each DS unit 36 that receives a slice 42-48 for storage translates thevirtual DSN memory address of the slice into a local physical addressfor storage. Accordingly, each DS unit 36 maintains a virtual tophysical memory mapping to assist in the storage and retrieval of data.

The first type of user device 12 performs a similar function to storedata in the DSN memory 22 with the exception that it includes the DSprocessing. As such, the device 12 encodes and slices the data fileand/or data block it has to store. The device then transmits the slices11 to the DSN memory via its DSN interface 32 and the network 24.

For a second type of user device 14 to retrieve a data file or datablock from memory, it issues a read command via its interface 30 to theDS processing unit 16. The DS processing unit 16 performs the DSprocessing 34 to identify the DS units 36 storing the slices of the datafile and/or data block based on the read command. The DS processing unit16 may also communicate with the DS managing unit 18 to verify that theuser device 14 is authorized to access the requested data.

Assuming that the user device is authorized to access the requesteddata, the DS processing unit 16 issues slice read commands to at least athreshold number of the DS units 36 storing the requested data (e.g., toat least 10 DS units for a 16/10 error coding scheme). Each of the DSunits 36 receiving the slice read command, verifies the command,accesses its virtual to physical memory mapping, retrieves the requestedslice, or slices, and transmits it to the DS processing unit 16.

Once the DS processing unit 16 has received a read threshold number ofslices for a data segment, it performs an error decoding function andde-slicing to reconstruct the data segment. When Y number of datasegments has been reconstructed, the DS processing unit 16 provides thedata file 38 and/or data block 40 to the user device 14. Note that thefirst type of user device 12 performs a similar process to retrieve adata file and/or data block.

The storage integrity processing unit 20 performs the third primaryfunction of data storage integrity verification. In general, the storageintegrity processing unit 20 periodically retrieves slices 45, and/orslice names, of a data file or data block of a user device to verifythat one or more slices have not been corrupted or lost (e.g., the DSunit failed). The retrieval process mimics the read process previouslydescribed.

If the storage integrity processing unit 20 determines that one or moreslices is corrupted or lost, it rebuilds the corrupted or lost slice(s)in accordance with the error coding scheme. The storage integrityprocessing unit 20 stores the rebuild slice, or slices, in theappropriate DS unit(s) 36 in a manner that mimics the write processpreviously described.

FIG. 2 is a schematic block diagram of an embodiment of a computing core26 that includes a processing module 50, a memory controller 52, mainmemory 54, a video graphics processing unit 55, an input/output (IO)controller 56, a peripheral component interconnect (PCI) interface 58,an IO interface 60, at least one IO device interface module 62, a readonly memory (ROM) basic input output system (BIOS) 64, and one or morememory interface modules. The memory interface module(s) includes one ormore of a universal serial bus (USB) interface module 66, a host busadapter (HBA) interface module 68, a network interface module 70, aflash interface module 72, a hard drive interface module 74, and a DSNinterface module 76. Note the DSN interface module 76 and/or the networkinterface module 70 may function as the interface 30 of the user device14 of FIG. 1. Further note that the IO device interface module 62 and/orthe memory interface modules may be collectively or individuallyreferred to as IO ports.

The processing module 50 may be a single processing device or aplurality of processing devices. Such a processing device may be amicroprocessor, micro-controller, digital signal processor,microcomputer, central processing unit, field programmable gate array,programmable logic device, state machine, logic circuitry, analogcircuitry, digital circuitry, and/or any device that manipulates signals(analog and/or digital) based on hard coding of the circuitry and/oroperational instructions. The processing module 50 may have anassociated memory and/or memory element, which may be a single memorydevice, a plurality of memory devices, and/or embedded circuitry of theprocessing module 50. Such a memory device may be a read-only memory,random access memory, volatile memory, non-volatile memory, staticmemory, dynamic memory, flash memory, cache memory, and/or any devicethat stores digital information. Note that if the processing module 50includes more than one processing device, the processing devices may becentrally located (e.g., directly coupled together via a wired and/orwireless bus structure) or may be distributedly located (e.g., cloudcomputing via indirect coupling via a local area network and/or a widearea network). Further note that when the processing module 50implements one or more of its functions via a state machine, analogcircuitry, digital circuitry, and/or logic circuitry, the memory and/ormemory element storing the corresponding operational instructions may beembedded within, or external to, the circuitry comprising the statemachine, analog circuitry, digital circuitry, and/or logic circuitry.Still further note that, the memory element stores, and the processingmodule 50 executes, hard coded and/or operational instructionscorresponding to at least some of the steps and/or functions illustratedin FIGS. 1-26.

FIG. 3 is a schematic block diagram of an embodiment of a dispersedstorage (DS) processing module 34 of user device 12 and/or of the DSprocessing unit 16. The DS processing module 34 includes a gatewaymodule 78, an access module 80, a grid module 82, and a storage module84. The DS processing module 34 may also include an interface 30 and theDSnet interface 32 or the interfaces 68 and/or 70 may be part of user 12or of the DS processing unit 14. The DS processing module 34 may furtherinclude a bypass/feedback path between the storage module 84 to thegateway module 78. Note that the modules 78-84 of the DS processingmodule 34 may be in a single unit or distributed across multiple units.

In an example of storing data, the gateway module 78 receives anincoming data object that includes a user ID field 86, an object namefield 88, and the data field 40 and may also receive correspondinginformation that includes a process identifier (e.g., an internalprocess/application ID), metadata, a file system directory, a blocknumber, a transaction message, a user device identity (ID), a dataobject identifier, a source name, and/or user information. The gatewaymodule 78 authenticates the user associated with the data object byverifying the user ID 86 with the managing unit 18 and/or anotherauthenticating unit.

When the user is authenticated, the gateway module 78 obtains userinformation from the management unit 18, the user device, and/or theother authenticating unit. The user information includes a vaultidentifier, operational parameters, and user attributes (e.g., userdata, billing information, etc.). A vault identifier identifies a vault,which is a virtual memory space that maps to a set of DS storage units36. For example, vault 1 (i.e., user 1's DSN memory space) includeseight DS storage units (X=8 wide) and vault 2 (i.e., user 2's DSN memoryspace) includes sixteen DS storage units (X=16 wide). The operationalparameters may include an error coding algorithm, the width n (number ofpillars X or slices per segment for this vault), a read threshold T, awrite threshold, an encryption algorithm, a slicing parameter, acompression algorithm, an integrity check method, caching settings,parallelism settings, and/or other parameters that may be used to accessthe DSN memory layer.

The gateway module 78 uses the user information to assign a source name35 to the data. For instance, the gateway module 60 determines thesource name 35 of the data object 40 based on the vault identifier andthe data object. For example, the source name may contain a fileidentifier (ID), a vault generation number, a reserved field, and avault identifier (ID). As another example, the gateway module 78 maygenerate the file ID based on a hash function of the data object 40.Note that the gateway module 78 may also perform message conversion,protocol conversion, electrical conversion, optical conversion, accesscontrol, user identification, user information retrieval, trafficmonitoring, statistics generation, configuration, management, and/orsource name determination.

The access module 80 receives the data object 40 and creates a series ofdata segments 1 through Y 90-92 in accordance with a data storageprotocol (e.g., file storage system, a block storage system, and/or anaggregated block storage system). The number of segments Y may be chosenor randomly assigned based on a selected segment size and the size ofthe data object. For example, if the number of segments is chosen to bea fixed number, then the size of the segments varies as a function ofthe size of the data object. For instance, if the data object is animage file of 4,194,304 eight bit bytes (e.g., 33,554,432 bits) and thenumber of segments Y=131,072, then each segment is 256 bits or 32 bytes.As another example, if segment sized is fixed, then the number ofsegments Y varies based on the size of data object. For instance, if thedata object is an image file of 4,194,304 bytes and the fixed size ofeach segment is 4,096 bytes, the then number of segments Y=1,024. Notethat each segment is associated with the same source name.

The grid module 82 receives the data segments and may manipulate (e.g.,compression, encryption, cyclic redundancy check (CRC), etc.) each ofthe data segments before performing an error coding function of theerror coding dispersal storage function to produce a pre-manipulateddata segment. After manipulating a data segment, if applicable, the gridmodule 82 error encodes (e.g., Reed-Solomon, Convolution encoding,Trellis encoding, etc.) the data segment or manipulated data segmentinto X error coded data slices 42-44.

The value X, or the number of pillars (e.g., X=16), is chosen as aparameter of the error coding dispersal storage function. Otherparameters of the error coding dispersal function include a readthreshold T, a write threshold W, etc. The read threshold (e.g., T=10,when X=16) corresponds to the minimum number of error-free error codeddata slices required to reconstruct the data segment. In other words,the DS processing module 34 can compensate for X−T (e.g., 16−10=6)missing error coded data slices per data segment. The write threshold Wcorresponds to a minimum number of DS storage units that acknowledgeproper storage of their respective data slices before the DS processingmodule indicates proper storage of the encoded data segment. Note thatthe write threshold is greater than or equal to the read threshold for agiven number of pillars (X).

For each data slice of a data segment, the grid module 82 generates aunique slice name 37 and attaches it thereto. The slice name 37 includesa universal routing information field and a vault specific field and maybe 48 bytes (e.g., 24 bytes for each of the universal routinginformation field and the vault specific field). As illustrated, theuniversal routing information field includes a slice index, a vault ID,a vault generation, and a reserved field. The slice index is based onthe pillar number and the vault ID and, as such, is unique for eachpillar (e.g., slices of the same pillar for the same vault for anysegment will share the same slice index). The vault specific fieldincludes a data name, which includes a file ID and a segment number(e.g., a sequential numbering of data segments 1-Y of a simple dataobject or a data block number).

Prior to outputting the error coded data slices of a data segment, thegrid module may perform post-slice manipulation on the slices. Ifenabled, the manipulation includes slice level compression, encryption,CRC, addressing, tagging, and/or other manipulation to improve theeffectiveness of the computing system.

When the error coded data slices of a data segment are ready to beoutputted, the grid module 82 determines which of the DS storage units36 will store the EC data slices based on a dispersed storage memorymapping associated with the user's vault and/or DS storage unitattributes. The DS storage unit attributes may include availability,self-selection, performance history, link speed, link latency,ownership, available DSN memory, domain, cost, a prioritization scheme,a centralized selection message from another source, a lookup table,data ownership, and/or any other factor to optimize the operation of thecomputing system. Note that the number of DS storage units 36 is equalto or greater than the number of pillars (e.g., X) so that no more thanone error coded data slice of the same data segment is stored on thesame DS storage unit 36. Further note that EC data slices of the samepillar number but of different segments (e.g., EC data slice 1 of datasegment 1 and EC data slice 1 of data segment 2) may be stored on thesame or different DS storage units 36.

The storage module 84 performs an integrity check on the outboundencoded data slices and, when successful, identifies a plurality of DSstorage units based on information provided by the grid module 82. Thestorage module 84 then outputs the encoded data slices 1 through X ofeach segment 1 through Y to the DS storage units 36. Each of the DSstorage units 36 stores its EC data slice(s) and maintains a localvirtual DSN address to physical location table to convert the virtualDSN address of the EC data slice(s) into physical storage addresses.

In an example of a read operation, the user device 12 and/or 14 sends aread request to the DS processing unit 14, which authenticates therequest. When the request is authentic, the DS processing unit 14 sendsa read message to each of the DS storage units 36 storing slices of thedata object being read. The slices are received via the DSnet interface32 and processed by the storage module 84, which performs a parity checkand provides the slices to the grid module 82 when the parity check wassuccessful. The grid module 82 decodes the slices in accordance with theerror coding dispersal storage function to reconstruct the data segment.The access module 80 reconstructs the data object from the data segmentsand the gateway module 78 formats the data object for transmission tothe user device.

FIG. 4 is a schematic block diagram of an embodiment of a grid module 82that includes a control unit 73, a pre-slice manipulator 75, an encoder77, a slicer 79, a post-slice manipulator 81, a pre-slice de-manipulator83, a decoder 85, a de-slicer 87, and/or a post-slice de-manipulator 89.Note that the control unit 73 may be partially or completely external tothe grid module 82. For example, the control unit 73 may be part of thecomputing core at a remote location, part of a user device, part of theDS managing unit 18, or distributed amongst one or more DS storageunits.

In an example of write operation, the pre-slice manipulator 75 receivesa data segment 90-92 and a write instruction from an authorized userdevice. The pre-slice manipulator 75 determines if pre-manipulation ofthe data segment 90-92 is required and, if so, what type. The pre-slicemanipulator 75 may make the determination independently or based oninstructions from the control unit 73, where the determination is basedon a computing system-wide predetermination, a table lookup, vaultparameters associated with the user identification, the type of data,security requirements, available DSN memory, performance requirements,and/or other metadata.

Once a positive determination is made, the pre-slice manipulator 75manipulates the data segment 90-92 in accordance with the type ofmanipulation. For example, the type of manipulation may be compression(e.g., Lempel-Ziv-Welch, Huffman, Golomb, fractal, wavelet, etc.),signatures (e.g., Digital Signature Algorithm (DSA), Elliptic Curve DSA,Secure Hash Algorithm, etc.), watermarking, tagging, encryption (e.g.,Data Encryption Standard, Advanced Encryption Standard, etc.), addingmetadata (e.g., time/date stamping, user information, file type, etc.),cyclic redundancy check (e.g., CRC32), and/or other data manipulationsto produce the pre-manipulated data segment.

The encoder 77 encodes the pre-manipulated data segment 92 using aforward error correction (FEC) encoder (and/or other type of erasurecoding and/or error coding) to produce an encoded data segment 94. Theencoder 77 determines which forward error correction algorithm to usebased on a predetermination associated with the user's vault, a timebased algorithm, user direction, DS managing unit direction, controlunit direction, as a function of the data type, as a function of thedata segment 92 metadata, and/or any other factor to determine algorithmtype. The forward error correction algorithm may be Golay,Multidimensional parity, Reed-Solomon, Hamming, Bose Ray ChauduriHocquenghem (BCH), Cauchy-Reed-Solomon, or any other FEC encoder. Notethat the encoder 77 may use a different encoding algorithm for each datasegment 92, the same encoding algorithm for the data segments 92 of adata object, or a combination thereof.

The encoded data segment 94 is of greater size than the data segment 92by the overhead rate of the encoding algorithm by a factor of X/T, whereX is the width or number of slices, and T is the read threshold. In thisregard, the corresponding decoding process can accommodate at most X-Tmissing EC data slices and still recreate the data segment 92. Forexample, if X=16 and T=10, then the data segment 92 will be recoverableas long as 10 or more EC data slices per segment are not corrupted.

The slicer 79 transforms the encoded data segment 94 into EC data slicesin accordance with the slicing parameter from the vault for this userand/or data segment 92. For example, if the slicing parameter is X=16,then the slicer 79 slices each encoded data segment 94 into 16 encodedslices.

The post-slice manipulator 81 performs, if enabled, post-manipulation onthe encoded slices to produce the EC data slices. If enabled, thepost-slice manipulator 81 determines the type of post-manipulation,which may be based on a computing system-wide predetermination,parameters in the vault for this user, a table lookup, the useridentification, the type of data, security requirements, available DSNmemory, performance requirements, control unit directed, and/or othermetadata. Note that the type of post-slice manipulation may includeslice level compression, signatures, encryption, CRC, addressing,watermarking, tagging, adding metadata, and/or other manipulation toimprove the effectiveness of the computing system.

In an example of a read operation, the post-slice de-manipulator 89receives at least a read threshold number of EC data slices and performsthe inverse function of the post-slice manipulator 81 to produce aplurality of encoded slices. The de-slicer 87 de-slices the encodedslices to produce an encoded data segment 94. The decoder 85 performsthe inverse function of the encoder 77 to recapture the data segment90-92. The pre-slice de-manipulator 83 performs the inverse function ofthe pre-slice manipulator 75 to recapture the data segment 90-92.

FIG. 5 is a diagram of an example of slicing an encoded data segment 94by the slicer 79. In this example, the encoded data segment 94 includesthirty-two bits, but may include more or less bits. The slicer 79disperses the bits of the encoded data segment 94 across the EC dataslices in a pattern as shown. As such, each EC data slice does notinclude consecutive bits of the data segment 94 reducing the impact ofconsecutive bit failures on data recovery. For example, if EC data slice2 (which includes bits 1, 5, 9, 13, 17, 25, and 29) is unavailable(e.g., lost, inaccessible, or corrupted), the data segment can bereconstructed from the other EC data slices (e.g., 1, 3 and 4 for a readthreshold of 3 and a width of 4).

FIG. 6 is a schematic block diagram of another embodiment of a computingsystem that includes a source user device 12, a plurality of destinationuser devices 1-D 12, a plurality of wireless modules 102-108, adispersed storage (DS) processing unit 16, and a dispersed storagenetwork (DSN) memory 22. Each of user devices 12 includes a computingcore 26 and a DSN interface 32, wherein the computing core 26 includes aDS processing 34. Each of the wireless modules 102-108 may be portabledevices (e.g., cell phone, tablet computer, radio, etc.) or fixeddevices (e.g., access point, cellular base station, a radio site, etc.)and each includes a radio frequency transceiver and baseband processingcircuitry. The wireless modules 102-108 operate in accordance with oneor more wireless industry standards including, but not limited to,universal mobile telecommunications system (UMTS), global system formobile communications (GSM), long term evolution (LTE), wideband codedivision multiplexing (WCDMA), IEEE 802.11, IEEE 802.16.

Note that a wireless broadcast service is provided by the wirelessmodule 102 by way of a common wireless resource including but notlimited to a common frequency division multiplexing frequency (e.g.,channel), a common time division multiplexing slot, a common codedivision multiplexing code, and/or a common frequency hopping sequence.In an example, all slice pillars produced from a common data object aretransmitted as wireless signals of a common wireless resource. Inanother example, each slice pillar produced from the same data object istransmitted as wireless signals via two or more wireless resources(e.g., two or more frequencies).

In an example of operation, the source user device 12 is contained in amobile vehicle (e.g., an aircraft, a ship, a truck, etc.) and isoperable to securely transmit audio/video (A/V) data (e.g., a live videostream, an image file, a video file, an audio file, a text file, a textcommunication, etc.) to one or more of the destination user devicesand/or to the DSN memory 22. In this example, the source user device 12receives the audio/video data from an A/V source (e.g., one or moredigital cameras, one or more microphones, etc.) and the DS processingmodule 34 encrypts the A/V data. The DS processing module 34 thenpartitions the encrypted data into data segments and encodes each of thedata segments using a dispersed storage error encoding function toproduce a plurality of sets of encoded data slices. Note that a set ofencoded data slices corresponds to a data segment of the encrypted data.

As the DS processing module 34 is producing sets of encoded data slices,it stores them until a threshold number of encoded data slices arestored. Once a threshold number of encoded data slices are stored, theDS processing module 34 outputs encoded data slices to the DSN interfacein accordance with a pseudo-random sequencing order. The pseudo-randomsequencing order insures that the encoded data slices of a set ofencoded data slices are not outputted sequentially, but are outputted ina random order with encoded data slices of other sets to add furthersecurity to the transmission of the A/V data. For example, thepseudo-random sequencing order randomly orders the data segments priorto dispersal storage error encoding and then randomly orders the encodeddata slices. As another example, the pseudo-random sequencing orderrandomly orders the encoded data slices.

The wireless module 102 converts the randomly ordered encoded dataslices into outbound RF signals in accordance with one or morestandardized wireless communication protocols or a proprietary wirelesscommunication protocol. For example, the baseband circuitry of thewireless module 102 converts an encoded data slice (a portion or anencoded data slice or multiple encoded data slices) into an outboundsymbol stream. The RF transceiver of the wireless module converts theoutbound symbol stream into an outbound RF signal.

At least one of the other wireless modules 104-108 receives the outboundRF signals of wireless module 102 and determines whether it is adestination. For example, the RF signals include destination addressinformation, which the receiving wireless modules interpret to determinewhether they are destinations. As another example, the RF signalsinclude source address information, which the receiving wireless modulesinterpret to determine whether they are destinations for the source.

When a wireless module 104-108 is a destination, it converts the RFsignals into the encoded data slices 110 and provides them to thecorresponding DS unit (e.g., user device 12 or DS processing unit 16).The corresponding DS unit uses a pseudo-random de-sequencing order tore-order the received encoded data slices into sets of encoded dataslices. The corresponding DS unit then decodes the set of encoded dataslices using a dispersal storage error decoding function to produce thedata segments, which are decrypted to re-produce the A/V data. To insuresecurity of the A/V data transmission, the pseudo-randomsequencing/de-sequencing order and the dispersal storage errorencoding/decoding function is securely communicated between the sourceuser device 12 and the corresponding destination unit(s) (e.g.,destination user devices and/or the DS processing unit).

FIG. 7 is a schematic block diagram of another embodiment of a dispersedstorage (DS) processing module 34 coupled to the DSnet interface 32 andthe processing module 50. The processing module 50 is coupled to one ormore data sources (e.g., camera, microphone, text messaging input, etc.)and the DSnet interface 32 is coupled to a wireless module 102. The DSprocessing module includes a storage module 138, a plurality ofinterfaces 114-118, a plurality of gateway modules 78, a plurality ofaccess modules 80, and a plurality of grid modules 182. The interfacemodules 114-118, the gateway modules 78, the access modules 89, and thegrid modules 82 are arranged in sets for processing different data(e.g., data 140-144), which includes A/V data from one or more datasources (e.g., cameras, computer, microphones, etc.) and/or auxiliarydata 144 (e.g., null data, authentication information, a next pseudorandom output sequencing order, a pseudo random output sequencing orderidentifier, a next outputting threshold, a random number generatoroutput, an encryption key, a starting point for the pseudo random outputsequencing order, a device identifier, a data identifier, a data type, adata size indictor, a priority indicator, a security indicator, and/or aperformance indicator).

In a first example of operation, one or more of the data sourcesprovides data to the processing module 50 and/or directly to the DSprocessing module 34. For example, a first digital camera provides astream of video directly to interface 114 of the DS processing module 50and a second camera provides A/V data to the processing module 50 forA/V processing (e.g., video encoding, video decoding, compression,aspect ratio conversion, etc.). The processing module 50 provides theprocessed A/V data to interface 116 of the DS processing module 34. Theprocessing module, or an auxiliary data source, may also generateauxiliary data 144, which is provided to interface 118 of the DSprocessing module 34.

Each set of gateway, access, and grid modules 78, 80, and 82 performtheir corresponding functions on the data 140, 142, or auxiliary data144, to produce one or more sets of slices 146-150. For instance and asdiscussed with reference to one or more of FIGS. 1-5, the gateway module78 accommodates a file system of a data source (e.g., a computing core)by translating a computer file system to a virtual dispersed storagenetwork (DSN) addressing (e.g., a source name). The access module 80converts the data 140-144 into sequential data segments (e.g., segment1, segment 2, segment 3, etc.). Alternatively, the access module 80converts the data 140-144 into non-sequential data segments (e.g.,segment 4, segment 1, segment 3, etc.) in accordance with a segmentsequence sequencing/de-sequencing order. The grid module 82 encrypts anddispersal storage error encodes a data segment into a set of encodeddata slices in a sequential order (e.g., pillar 0 slice 1, pillar 0slice 2 etc., pillar 1 slice 1, pillar 1 slice 2 etc.). Alternatively,the grid module 82 encrypts and dispersal storage error encodes datasegments into sets of encoded data slices and outputs the encoded dataslices in accordance with the pseudo random sequencing/de-sequencingorder (e.g., pillar 4 slice 8, pillar 2 slice 3 etc., pillar 5 slice 4,pillar 0 slice 2 etc.).

The storage module 138 receives the sets of encoded data slices 146-150and outputs encoded data slices in accordance with the pseudo randomsequencing/de-sequencing order. The random outputting of encoded dataslices may be done in combination with the segment sequencing performedby the access module 80, in combination with encoded data slice outputrandomize sequencing performed by the gird module 82, done without thesequencing performed by the access module or grid module, and/or acombination thereof.

As an example of the pseudo random sequencing/de-sequencing order, thestorage module selects ten slices from set 1 (e.g., a set from the sets146) followed by five slices from set 2 (e.g., a set from sets 148)followed by one slice from set 3 (e.g., a set from sets 150) etc. Thestorage module 138 may determine the random sequence and the startingpoint for the random sequence via a selection sequence generator and aseed. The seed and/or the identity of the random sequence may beincluded in the auxiliary data, may be embedded in the data 140, 142,and/or may be communicated using another secure mechanism.

In a second example of operation, the storage module 138 receivesrandomly ordered encoded data slices 110 and outputs sets of encodeddata slices in accordance with the pseudo randomsequencing/de-sequencing order. The grid module 82 decodes the set ofencoded data slices 146-150 in accordance with a dispersal storage errordecoding function to produce encrypted data segments, which it decryptsto produce data segments. Alternatively, the grid module 82 may re-orderthe sets of slices in accordance with the pseudo randomsequencing/de-sequencing order prior to dispersal storage errordecoding.

The access module 80 converts the data segments into the data 140-144.Alternatively, the access module 80 reorders the data segments inaccordance with a segment sequence sequencing/de-sequencing order andthen produces the data. The gateway module 78 translates the virtualdispersed storage network (DSN) addressing (e.g., a source name) into acomputer file system name. The processing module 50 receives the data140-144, processes it, and/or provides it to a data destination (e.g., avideo monitor, a speaker, DSN memory, etc.).

FIG. 8A is a schematic block diagram of an embodiment of a storagemodule 138 that includes a plurality of sequencers 160-164, a pluralityof sequence generators 166-170, a plurality of de-sequencers 172-176, aplurality of de-sequence generators 178-182, a selector 184, a selectionsequence generator 188, a de-selector 186, and a de-selectionde-sequence generator 190.

In an example of operation, the storage module 138 receives sets ofencoded data slices 192-196 from the plurality of grid modules 82. Eachsequencer 160-162 converts its sets of encoded data slices into randomlyordered sets of encoded data slices accordance with a pseudo randomsegment and/or slice sequence generated by the corresponding sequencegenerators 166-170. For instance, the sequence generators generate arandom sequence based on a seed that reorders the corresponding sets ofencoded data slices, reorders slices within a set of slices, and/orreorders slices and sets of slices. Alternatively, the sequencegenerator generates a null sequence such that the sequencer outputs theencoded data slices in the order they were received (i.e., first in,first out).

The selector 184 selects slices from sequencers 160-164 in accordancewith a selection sequence. The selection sequence generator 188generates the selection sequence in accordance with the pseudo randomsequencing/de-sequencing order. As a specific example, the selectsequence generator 188 generates a selection sequence that causes theselector 184 to select ten slices from sequencer 160, then five slicesfrom sequencer 162, and then three slices from sequencer 164, which aresubsequently outputted as output sequenced slices 204.

In another example of operation, the de-selector 186 receives inputsequenced slices 206 and provides them to the de-sequencers 172-176 inaccordance with a de-sequence order. The de-selection de-sequencegenerator 190 generates the de-sequence order in accordance with thepseudo random sequencing/de-sequencing order. As a specific example, thede-selection de-sequence generator 190 generates the de-sequence ordersuch that the de-selector 186 sends ten slices of the input sequencedslices 206 to de-sequencer 172, the five slices to de-sequencer 174, andthen three slices to de-sequencer 176.

Each of the de-sequencers 172-176 produces sets of encoded data slicesas ordered output slices 198-202 in accordance with a slice and/orsegment de-sequence order that is generated by a correspondingde-sequence generator 178-182. For instance, the de-sequence generatorsgenerate a random sequence based on a seed that reorders the receivedslices into sets of encoded data slices. Alternatively, the de-sequencegenerator generates a null sequence such that the de-sequencer outputsthe encoded data slices in the order they were received (i.e., first in,first out).

The segment and/or slice sequence/de-sequence order may be part of thepseudo random sequencing/de-sequencing order. In addition, each pair ofsequence generators and de-sequence generators may generate the samesequence/de-sequence order or different sequence/de-sequence orders.Further, the pseudo random sequencing/de-sequencing order includes oneor more of one or more slice sequence/de-sequence orders, a selectionsequence/de-sequence, a sequence/de-sequence seed determination, one ormore sequence/de-sequence seeds. Still further, the pseudo randomsequencing/de-sequencing order may be determined based on one or more ofa performance indicator, a security indicator, a security indicator,sequence information, a key, a user device identifier (ID), a lookup, alist, a command, a predetermination, a message, an algorithm, a dataobject, a data object ID, a data type, a data size, and a hash of thedata. Even further, the pseudo random sequencing/de-sequencing order maybe generated by any one of a variety of pseudo random number generationtechniques that may be implemented in software, programmable logic,and/or a state machine.

FIG. 8B is a diagram illustrating an example of pseudo randomsequencing/de-sequencing of encoded data slices within the storagemodule 138 for two different data streams (e.g., data 1 and data 2). Inthis example, an encrypted data segment is dispersal storage errorencoded into five encoded data slices. For instance, data segment 1 ofdata 1 is encoded into five encoded data slices (e.g., data 1, segment1, slice 1, through data 1, segment 1, slice 5).

For pseudo random sequencing, the storage module 138 receives theencoded data slices of data 1 and data 2, stores them, and when athreshold number (e.g., X times the pillar width, which, for thisexample is 6 times 5=30) applies the pseudo random sequencing order torandomize the outputting of the encoded data slices. In this example,the pseudo random sequencing/de-sequencing order randomizes the encodeddata slices are sequenced and selected to produce slices in order ofdata 2, segment 2, slice 3 followed by data 1, segment 1, slice 3,followed by data 1, segment 2, slice 1, followed by data 2, segment 3,slice 2, followed by data 2, segment 1, slice 4, etc.

For pseudo random de-sequencing, the storage module 138 receives therandomized encoded data slices, stores them until a threshold number arestored, and then applies the pseudo random de-sequencing order toreproduce the encoded data slices 205 of data 1 and the encoded dataslices 207 of data 2. The storage module 138 may output the de-sequencedencoded data slices are they are de-sequenced or store a data segment'sworth of slices and then send the set of encoded data slices.

FIG. 8C is a diagram illustrating an example of pseudo randomsequencing/de-sequencing of encoded data slices within the storagemodule 138 for two different data streams (e.g., data 1 and data 2,which may be auxiliary data). In this example, the access module 80 ofthe DS processing module 80 randomized the data segments prior to thegrid module 82 dispersal storage error encoding the data segments. Therandomizing of the data segments may be different for each data path orit may be the same.

In the present example, the data segments of the first data path arerandomized using a first segment sequence to produce, for three datasegments, a randomized data segment order of 3, 1, 2. The data segmentsof the second data path are randomized using a second segment sequenceto produce, for three data segments, a randomized data segment order of2, 1, 3. The storage module 138 randomizes and de-randomizes the encodeddata slices of the randomized data segments using the pseudo randomsequencing/de-sequencing order as previously discussed.

FIG. 8D is a diagram illustrating an example of pseudo randomsequencing/de-sequencing of encoded data slices within the storagemodule 138 for two different data streams (e.g., data 1 and data 2). Inthis example, the grid module 82 of the DS processing module 80randomized the encoded data slices for each data segment it dispersalstorage error encodes. The randomizing of the encoded data slices may bedifferent for each data path or it may be the same. The randomizing ofthe encoded data slices may also be the same or different for each datasegment.

In the present example, each of the data segments of the first andsecond data paths are randomized using the same sequence to produce, forfive encoded data slices per data segment, a randomized encoded datasegment order of 2, 1, 5, 4, 3. The storage module 138 randomizes andde-randomizes the randomized encoded data slices using the pseudo randomsequencing/de-sequencing order as previously discussed.

FIG. 8E is a diagram illustrating an example of pseudo randomsequencing/de-sequencing of encoded data slices within the storagemodule 138 for two different data streams (e.g., data 1 and data 2). Inthis example, an encrypted data segment is dispersal storage errorencoded into five encoded data slices, but, for at least some of thedata segments, less than all of the encoded data slices will beoutputted. For instance, the first encoded data slice of data segment 1of data 1 will not be outputted; the fourth encoded data slice of datasegment 2 of data 1 will not be outputted; the second and fifth encodeddata slices of data segment 3 of data 1 will not be outputted; thesecond encoded data slice of data segment 1 of data 2 will not beoutputted; and the third encoded data slice of data segment 2 of data 2will not be outputted.

For pseudo random sequencing, the storage module 138 receives theencoded data slices of data 1 and data 2, stores them, and when athreshold number applies the pseudo random sequencing order to randomizethe outputting of the encoded data slices. When the storage module 138reaches one of the encoded data slices that is not to be outputted, itoutputs a null data slice or repeats one of the other encoded dataslices.

For pseudo random de-sequencing, the storage module 138 receives therandomized encoded data slices, stores them until a threshold number arestored, and then applies the pseudo random de-sequencing order toreproduce the encoded data slices 205 of data 1 and the encoded dataslices 207 of data 2, less the omitted encoded data slices. When thestorage module 138 outputs a set of encoded data slices that includesone or more omitted encoded data slices, it may output the set withoutthe omitted encoded data slice(s) or it may output a null data slice inthe place of the omitted encoded data slice.

The examples of FIGS. 8B-8E are equally applicable for data from asingle source. In this instance, the pseudo randomsequencing/de-sequencing order is applied to sets of encoded data slicesof data segments of data from a single source.

FIG. 9 is a flowchart illustrating an example of encoding data toproduce encoded data slices. The method begins with step 210 where aprocessing module receives a store data object message from one or moreof a computing core, a user device, a dispersed storage (DS) processingunit, a storage integrity processing unit, a DS managing unit, a DSunit, and a process or function of a user device. The store data objectmessage includes a requester identifier (ID) (e.g., a source user deviceID), a target ID (e.g., a destination user device ID), a data objectname, data, a data stream (e.g., a video stream), sequence information,a key (e.g., an encryption key), a priority indicator, a securityindicator, and/or a performance indicator.

The method continues at step 212 where the processing module determinesone or more sets of error coding dispersal storage function parametersregarding the data of the data object message and for auxiliary data.For example, one set of error coding dispersal storage functionparameters may be determined for the data and another set may bedetermined for the auxiliary data. As another example, the same errorcoding dispersal storage function parameters are determined for both thedata and the auxiliary data.

The method continues at step 214 where the processing module segmentsthe data in accordance with the error coding dispersal storage functionparameters. The processing module segments the data into data segments,which may be outputted in a variety of ways. For example, the processingmodule outputs the data segments in the order in which they were created(i.e., sequentially). As another example, the processing module outputsthe data segments in accordance with a segment sequencing order (i.e.,pseudo randomly non-sequential).

The method continues at step 216 where the processing module dispersedstorage error encodes the data segments to produce sets of encoded dataslices (e.g., one set per data segment). The processing module mayoutput the sets of encoded data slices in a variety of ways. Forexample, the processing module outputs the encoded data slices of a setin the order in which they were created (i.e., sequentially). As anotherexample, the processing module outputs the encoded data slices of a setin accordance with a segment sequencing order (i.e., pseudo randomlynon-sequential). As yet another example, the processing module outputs athreshold number of a set of encoded data slices (e.g., a readthreshold, a write threshold, a decode threshold, etc.). As a furtherexample, the processing module buffers a set of encoded data slices intwo buffers: the first including a threshold number of encoded dataslices and the second including the remaining encoded data slices. Inthis example, the processing module outputs the encoded data slices ofthe first buffer and outputs zero to all of the encoded data slices ofthe second buffer.

At step 216, the processing module may also generate a slice name foreach encoded data slices of a set. The processing module determinesslice information for a set of encoded data slices and encrypts theslice information to produce the slice name, which may be buffered.

The method continues at step 218 where the processing module determinesa pseudo-random sequencing order and/or sequence information. Forexample, the processing module determines a pseudo-random sequencingorder associated with algorithm 3AC (e.g. a pseudo random numbergeneration algorithm), a sequence seed of 1F46D8EA39B based on acalculating a hash over requester ID 5F02D77B, and a key of 34D8AB90,which was embedded in the sequencing information.

The method continues at step 220 where the processing module sequencesthe outputting of encoded data slices in accordance with thepseudo-random sequencing order.

For example, the processing module buffers encoded data slices of thesets until a threshold number have been buffered. When a thresholdnumber of slices have been buffered, the processing module outputs theencoded data slices based on the pseudo-random sequencing order; exampleof which were discussed with reference to FIGS. 8B-8E.

The method continues at step 222 where the processing module dispersalstorage error encodes auxiliary data using the parameters determined atstep 212 to produce one or more sets of encoded auxiliary data slices.The auxiliary data, which may be encrypted using one or more theencrypting functions discussed herein prior to dispersal storage errorencoding, includes null data, authentication information, a next pseudorandom output sequencing order, a pseudo random output sequencing orderidentifier, a next outputting threshold, a random number generatoroutput, an encryption key, a starting point for the pseudo random outputsequencing order, a device identifier, a data identifier, a data type, adata size indictor, a priority indicator, a security indicator, and/or aperformance indicator. For example, a video stream is the data of steps214 & 216 and a next pseudo random output sequencing order is theauxiliary data.

The method continues at step 224 where the processing module determinesauxiliary data sequence information (i.e., a pseudo-random sequencingorder). The method continues at step 226 where the processing modulesequences outputting of the encoded auxiliary data slices, which may besimilar to sequencing the outputting of the encoded data slices.

The method continues at step 228 where the processing module determinesselection information, which includes a pseudo random output sequencingorder, a selection algorithm ID, a de-selection algorithm ID, a seedgeneration algorithm ID, a key, an ID, a hash algorithm, and/or asequence seed. The method continues at step 230 where the processingmodule selects encoded data slices and encoded auxiliary data slices toproduce output sequenced slices in accordance with the selectioninformation. The method continues at step 232 where processing moduletransmits the output sequenced slices to one or more destinations via awired and/or wireless network.

In addition, at step 232, the processing module may compare an ingressnumber of encoded data slices being buffered to an egress number ofencoded data slices being outputted within a given time interval when anumber of buffered encoded data slices compares favorably to thethreshold. Next, the processing module adjusts the dispersed storageerror encoding of the data segment such that the comparing of theingress number to the egress number is favorable with respect to anunderflow threshold when the comparing of the ingress number to theegress number is unfavorable with respect to the underflow threshold.Alternatively, the processing module may adjust the dispersed storageerror encoding of the data segment such that the comparing of theingress number to the egress number is favorable with respect to anoverflow threshold when the comparing of the ingress number to theegress number is unfavorable with respect to the overflow threshold.

FIG. 10 is a flowchart illustrating an example of decoding encoded dataslices to produce data. The method begins with step 234 where aprocessing module receives a retrieve data object message from one ormore of a computing core, a user device, a dispersed storage (DS)processing unit, a storage integrity processing unit, a DS managingunit, a DS unit, and a process or function of a user device). Theretrieve data object message includes one or more of a requesteridentifier (ID) (e.g., a source user device ID), a target ID (e.g., adestination user device ID), a data object name, a data object, sequenceinformation, a key (e.g., an encryption key), a priority indicator, asecurity indicator, and a performance indicator.

The method continues at step 236 with the processing module determineserror coding dispersal stored function parameters as previouslydiscussed. The method continues at step 238 where the processing moduleobtains at least an ordering threshold number of encoded data slices toproduce obtained encoded data slices from a user device, from DSNmemory, etc.

The method continues at step 240 where the processing module determinesde-selection information, which is the compliment to the selectioninformation and is determined in a similar fashion. The method continuesat step 242 where the processing module de-selects input sequencedslices (e.g., the received randomized encoded data slices) in accordancewith the de-selection information. For example, this separatesrandomized encoded data slices from the randomized encoded auxiliarydata slices.

The method continues at step 244 where the processing module determinesauxiliary data de-sequence information, which is complimentary to theauxiliary data sequence information. The method continues at step 246where the processing module de-sequences the sequenced (i.e.,randomized) encoded auxiliary data slices to produce de-sequencedencoded auxiliary data slices. The method continues at step 248 wherethe processing module recreates the auxiliary data from the de-sequencedencoded auxiliary data slices in accordance with the auxiliary errorcoding dispersal storage function parameters. If the auxiliary data wasencrypted, this step further includes decrypting the auxiliary data.

The method continues at step 250 where the processing module processesthe auxiliary data in accordance with one or more of the auxiliary errorcoding dispersal storage function parameters, a flag, a command, alookup, and the de-sequence information. For example, the processingmodule discards at least some of the auxiliary data when the de-sequenceinformation indicates that the auxiliary data contains random numbers.In another example, the processing module subsequently de-sequencessequenced encoded data slices a sequence seed contained within theauxiliary data when the de-sequence information indicates that theauxiliary data contains the sequence seed. In another example, theprocessing module subsequently de-sequences sequenced encoded dataslices of desired data utilizing de-sequence information containedwithin the auxiliary data when the de-sequence information indicatesthat the auxiliary data contains the de-sequence information.

The method continues at step 252 where the processing module determinesdata de-sequence information, which is complimentary to the datasequence information. The method continues at step 254 where theprocessing module orders (e.g., de-sequences) the randomized encodeddata slices based on the pseudo-random de-sequencing order to produce aplurality of sets of encoded data slices. The method continues at step256 where the processing module dispersed storage error decodes theplurality of sets of encoded data slices to produce a plurality of datasegments in accordance with the error coding dispersal storage functionparameters.

The method continues at step 258 where the processing module aggregatesthe plurality of data segments to produce the data (e.g., a data streamor one or more data objects). The processing module may aggregate theplurality of data segments by ordering them in accordance with a datasegment order of the pseudo-random de-sequencing order. The methodcontinues at step 260 where the processing module sends the data to arequester.

FIG. 11 is another flowchart illustrating another example of encodingdata to produce encoded data slices, which includes many similar stepsto FIG. 9. The method begins with steps 210-214 of FIG. 9 and thencontinues with step 268 where, in order of receiving data segments, theprocessing module encrypts a data segment of the to produce an encrypteddata segment. The processing module may encrypt the data segment usingone or more encrypting functions, which include an all or nothingtransformation (AONT), a stored encryption key and an encryptionalgorithm, a random encryption and an encryption algorithm, anencryption key associated with at least one recipient and an encryptionalgorithm, an obfuscating method, and/or a null encryption method.

As a specific example, the processing module encrypts the data segmentutilizing an all or nothing transformation (AONT) to produce anencrypted data segment. The processing module then calculates a hash ofthe encrypted data segment utilizing a hash function (e.g., secure hashfunction SHA-256, SHA-512 etc.), which may use a secret key. Theprocessing module truncates the encrypted data hash to match the numberof bits of the secret key, or other key. The processing modulecalculates an exclusive OR (XOR) of the key and the (truncated)encrypted data hash to produce a masked key. The processing moduleappends the masked key to the encrypted data segment, which issubsequently dispersal storage error encoded.

The method continues at step 270 where the processing module dispersedstorage error encodes the encrypted data segments to sets of encodeddata slices. The method concludes with steps 218-232 of FIG. 9.

FIG. 12 is another flowchart illustrating another example of decodingencoded data slices to produce data, which includes similar steps to theflowchart of FIG. 10. The method begins with steps 234-256 of FIG. 10and then continues with step 312 where the processing module decryptsthe encrypted data segments of step 256 to produce a plurality of datasegments. The decrypting includes the complement of the encryptingfunction used to encrypt the data segments.

For example, if the data segments were encrypted using the AONTencryption method, the processing module utilizes the AONT method todecrypt the encrypted data segment packages. As a more specific example,the processing module uses the AONT method and a key (e.g., a randomkey) to decrypt each encrypted data segment based on the random key usedto decrypt at least one encrypted auxiliary data segment associated withthe auxiliary data. The method concludes with steps 258-260 of FIG. 10.

FIG. 13 is another flowchart illustrating another example of encodingdata to produce encoded data slices, which includes many similar stepsto FIG. 9. The method begins with steps 210-214 of FIG. 9 and thencontinues with step 324 where the processing module determines a datasegment type (e.g., content) of a data segment. The data segment typeincludes one or more of a file header, a video header, routinginformation, addressing information, compression information, sourceinformation, destination information, video, text, music, speech, audio,telemetry, control information, a command, a request, statusinformation, a random number, a sequence seed, a key, a private key, ashared key, a secret key, a public key, and an image. Such adetermination may be based on one or more of the data segment, a datasegment type determination algorithm, the error coding dispersal storagefunction parameters, a requester identifier (ID), a vault lookup, a dataobject name, a data object, a data stream, sequence information, a key,a priority indicator, a security indicator, a command, apredetermination, a message, a performance indicator, and informationreceived in the store data object message.

The method continues at step 326, where, in order of receiving the datasegments, the processing module selects an encryption method based onthe data type (e.g., data segment type) and encrypts the data segmentusing the selected encryption method to produce an encrypted datasegment. Such a selection of the encryption method may be based on oneor more of the data segment type, the data segment, an encryption methoddetermination algorithm, the error coding dispersal storage functionparameters, a requester ID, a vault lookup, a data object name, a dataobject, a data stream, sequence information, a key, a priorityindicator, a security indicator, a command, a predetermination, amessage, the performance indicator, and information received in thestore data object message.

For example, the processing module encrypts the data segment utilizingan all or nothing transformation (AONT) encryption method when the datasegment type indicates that the type is a video header and the securityindicator indicates to encrypt video headers. In another example, theprocessing module determines not to encrypt the data segment when thedata segment type indicates that the type is routine status informationand the security indicator indicates to not encrypt routine statusinformation. In another example, the processing module selects theencryption method to include encrypting the data segment utilizing a keybased on a calculation of a hash value (e.g., secure hash functionSHA-256, SHA-512 etc.) over a key of the day, a source user ID, and acurrent time value. The method concludes with steps 218-232 of FIG. 10.

FIG. 14 is another flowchart illustrating another example of decodingencoded data slices to produce data, which includes similar steps to theflowchart of FIG. 10. The method begins with steps 234-256 of FIG. 10and then continues with step 370 where the processing module determinesa data segment type of a data segment. The processing module maydetermine the data segment type based on one or more of the data segmenttype extracted from the auxiliary data, from the sets of encoded dataslices, from the encrypted data segments, the encrypted data segment, adata segment type determination algorithm, the error coding dispersalstorage function parameters, a requester ID, a vault lookup, a dataobject name, a data object, a data stream, sequence information, a key,a priority indicator, a security indicator, a command, apredetermination, a message, a performance indicator, and informationreceived in the store data object message.

The method continues at step 372 where the processing module selects adecryption method based on the data segment type and decrypts theencrypted data segments utilizing the decryption method to produce theplurality of data segments. Note that the decryption method may varyfrom encrypted data segment to encrypted data segment. The methodconcludes with steps 258 and 260 of FIG. 10.

FIG. 15 is another flowchart illustrating another example of encodingdata to produce encoded data slices, which includes similar steps fromthe flowcharts of FIGS. 9 and 11. The method begins with steps 210-214of FIG. 9, step 268 of FIG. 11, and steps 216-220 of FIG. 9. The methodcontinues at step 392 where the processing module scrambling auxiliarydata segments to produce scrambled auxiliary data segments utilizing alow processing utilization scrambling algorithm. The low processingutilization scrambling algorithm may include one or more of rearrangingauxiliary data segment bits in accordance with a predetermined bitrearranging method, inverting all of the auxiliary data segment bits,inverting a portion of the auxiliary data segment bits in accordancewith a predetermined method, and rearranging a portion of the auxiliarydata segment bits in accordance with the predetermined bit rearrangingmethod and inverting a portion of the auxiliary data segment bits inaccordance with a predetermined bit inversion method. The processingmodule then dispersed storage error encodes the scrambled auxiliary datasegments to produce encoded auxiliary data slices in accordance withauxiliary error coding dispersal storage function parameters aspreviously discussed. The method concludes with steps 224-232 of FIG. 9.

FIG. 16 is another flowchart illustrating another example of decodingencoded data slices to produce data, which includes similar steps fromthe flowcharts of FIGS. 10 and 12. The method begins with steps 234-246of FIG. 10 and continues with step 418 where the processing moduledispersed storage error decodes the de-sequenced encoded auxiliary dataslices to produce scrambled auxiliary data segments. The processingmodule de-scrambles (e.g., the compliment of the scrambling) thescrambled auxiliary data segments to produce auxiliary data segments inaccordance with a de-scrambling algorithm. The processing moduleaggregates the auxiliary data segments to produce the auxiliary data.The method concludes with steps 250-256 of FIG. 10, step 312 of FIG. 12,and steps 258-260 of FIG. 10.

FIG. 17 is another flowchart illustrating another example of encodingdata to produce encoded data slices, which includes similar steps fromthe flowcharts of FIGS. 9 and 11. The method begins with steps 210-214of FIG. 9 and continues at step 440 where the processing moduledetermines an obfuscating method based on one or more of the errorcoding dispersal storage functions parameters, a requester identifier(ID), a vault lookup, a data object name, a data object, a data stream,sequence information, a key, a priority indicator, a security indicator,a command, a predetermination, a message, information in the store dataobject message, and a performance indicator. The obfuscating method mayinclude one or more of adding random bits (e.g., creation of a new datasegment that contains all of the bits of at least one receive datasegment of the received data segments and new random bits), invertingbits of the received data segment, and replacing a portion of the bitsof the received data segment with bits produced from a obfuscationcalculation based on the portion of bits of the received data segment(e.g., a logical XOR of the data segment bits with a key). The methodconcludes with step 268 of FIG. 11 and sets 218-232 of FIG. 9.

FIG. 18 is another flowchart illustrating another example of decodingencoded data slices to produce data, which includes similar steps fromthe flowcharts of FIGS. 10 and 12. The method begins with steps 234 -256of FIG. 10 and step 312 of FIG. 12. The method continues at step 488where the processing module determines a de-obfuscating method (e.g.,the compliment of the obfuscating method). The processing module maydetermine the de-obfuscating method may be based on one or more of theerror coding dispersal storage function parameters, a requesteridentifier (ID), a vault lookup, a data object name, a data object, adata stream, sequence information, a key, a priority indicator, asecurity indicator, a command, a predetermination, a message,information in the store data object message, and a performanceindicator. The method concludes with steps 258-260 of FIG. 10.

FIG. 19 is another flowchart illustrating another example of encodingdata to produce encoded data slices, which includes similar steps fromthe flowcharts of FIGS. 9 and 11. The method begins with steps 210-214of FIG. 9 and continues at step 500 where the processing moduledetermines a secret key. Such a determination may be based on one ormore of retrieval from a memory, a list, a lookup, a command, a message,a predetermination, and a calculation. Note that the processing modulemay determine a secret key for each data segment of the received datasegments. In an example, the processing module calculates the secret keyby hashing a key of the day, a user device identifier (ID), and acurrent date value.

The processing module encrypts the data segment in accordance withencryption algorithm utilizing the secret key to produce an encrypteddata segment as a data segment of the received data segments. Theprocessing module may determine a second key based on one or more ofretrieval from a memory, a list, a lookup, a command, a message, apredetermination, and a calculation. For example, the processing moduledetermines the second key as a public key from a lookup subsequent toreceiving the public key and storing it in a memory. The processingmodule encrypts the secret key in accordance with the error codingdispersal storage option parameters utilizing the second key to producean encrypted secret key and appends the encrypted secret key to anassociated encrypted data segment and/or to one or more encoded dataslices of the associated encrypted data segment. The method concludeswith step 268 of FIG. 11 and steps 218-232 of FIG. 9.

FIG. 20 is another flowchart illustrating another example of decodingencoded data slices to produce data, which includes similar steps fromthe flowcharts of FIGS. 10 and 12. The method begins with steps 234-256of FIG. 10 and step 312 of FIG. 12. The method continues at step 548where the processing module extracts an encrypted secret key from theencrypted data segment and/or from at least one of the encoded dataslices of the encrypted data segment. The processing module determines asecond key based on one or more of a retrieval from a memory, a list, alookup, a command, a message, a predetermination, and a calculation.

The processing module decrypts the encrypted secret key in accordancewith the error coding dispersal storage function parameters (e.g., aspecified decryption algorithm) utilizing the second key to produce areceived secret key. The processing module determines a secret key basedon one or more of the received secret key, retrieval from a memory, alist, a lookup, a command, a message, a predetermination, and acalculation. The processing module decrypts each of the furtherencrypted data segment (e.g., after the AONT method) in accordance withthe error coding dispersal storage function parameters (e.g., adecryption algorithm) utilizing the corresponding secret key. The methodconcludes with steps 258-260 of FIG. 10.

FIG. 21 is another flowchart illustrating another example of encodingdata to produce encoded data slices, which includes similar steps fromthe flowcharts of FIGS. 9 and 11. The method begins with steps 210-214of FIG. 9, step 268 of FIG. 11, and steps 216-218 of FIG. 9. The methodcontinues at step 566 where the processing module determines a sequenceseed based on one or more of the sequence information, a seed generationalgorithm, a hash function, a received key, a stored key, a calculatedkey, a data type (e.g., video, audio, telemetry, commands, statusinformation, etc.), a requester identifier (ID), a vault lookup, a dataobject name, a data object, a data stream, received sequence information(e.g., part of the request message), the error coding dispersal storagefunction parameters, information received in the store data objectrequest message, a calculation, a priority indicator, a securityindicator, a list, a command, a predetermination, a message, a previousseed, a last seed, a previous seed, and a performance indicator. Forexample, the processing module determines the sequence seed to include acalculated (e.g., hash) value of 1F46D8EA39B based on a hash over asource user device 5F02D77B, a key 34D8AB90, a sequence algorithm 3AC,and a video data type. The method concludes with steps 220-234 of FIG.9.

FIG. 22 is another flowchart illustrating another example of decodingencoded data slices to produce data, which includes similar steps fromthe flowcharts of FIGS. 10 and 12. The method begins with steps 234-252of FIG. 10 and continues at step 602 here the processing moduledetermines a de-sequence seed based on one or more of the de-sequenceinformation, a seed generation algorithm, a hash function, a receivedkey, a stored key, a calculated key, a data type (e.g., video, audio,telemetry, commands, status information, etc.), a requester identifier(ID), a vault lookup, a data object name, auxiliary data, a receivedsequence information (e.g., part of the request message), the errorcoding dispersal storage function parameters, information received inthe retrieve data object request message, a calculation, a priorityindicator, a security indicator, a list, a command, a predetermination,a message, a previous seed, a last seed, and a performance indicator.For example, the processing module determines the de-sequence seed toinclude a calculated (e.g., hash) value of 1F46D8EA39B based on a hashover a source user device 5F02D77B, a key 34D8AB90, a sequence algorithm3AC, and a video data type.

The method continues at step 254 where the processing module orders theencoded data slices based on a pseudo-random de-sequencing order usingthe de-sequence seed. The method concludes with step 312 of FIG. 12 andsteps 258-260 of FIG. 10.

FIG. 23 is another flowchart illustrating another example of encodingdata to produce encoded data slices, which includes similar steps fromthe flowcharts of FIGS. 9 and 11. The method begins with steps 210-214of FIG. 9, step 268 of FIG. 11, and steps 216-218 of FIG. 9. The methodcontinues at step 626 where the processing module determines a sequenceseed, an encryption key or seed, which it appends to one or more datasegments. In this step, the processing module encrypts the sequence seedutilizing the encryption key to produce an encrypted sequence seed. Notethat the encryption key may be varied from data segment to data segment.Alternatively, or in addition to, the processing module may include thesequence seed as data of the auxiliary data. The method concludes withsteps 220-232 of FIG. 9.

FIG. 24 is another flowchart illustrating another example of decodingencoded data slices to produce data, which includes similar steps fromthe flowcharts of FIGS. 10 and 12. The method begins with steps 234-252of FIG. 10 and continues at step 662 where the processing moduleextracts an appended encrypted sequence seed from one or more of aauxiliary data segment, and encoded auxiliary data slice, and an encodedand sliced to produce an encrypted de-sequence seed. The processingmodule decrypts the encrypted de-sequence seed in accordance utilizing aprivate key (e.g., of a public/private key pair of an associateddestination user device) to produce a decrypted de-sequence seed. In anexample, the processing module determines the de-sequence seed toinclude a value of 1F46D8EA39B based on the decrypted de-sequence seed.In another example, the processing module determines the de-sequenceseed to include a calculated (e.g., hash) value of 1F46D8EA39B based ona hash over a source user device 5F02D77B, a key 34D8AB90, a sequencealgorithm 3AC, and a video data type.

The method continues at step 254 where the processing module orders theencoded data slices based on a pseudo-random de-sequencing orderutilizing the de-sequence seed. The method concludes with step 256 ofFIG. 10, step 312 of FIG. 12, and steps 258-260 of FIG. 10.

FIG. 25 is another flowchart illustrating another example of encodingdata to produce encoded data slices, which includes similar steps fromthe flowcharts of FIGS. 9, 11, and 21. The method begins with steps210-214 of FIG. 9, step 268 of FIG. 11, steps 216-218 of FIG. 9, step566 of FIG. 21, and steps 220-230 of FIG. 9. The method continues atstep 700 where processing module sends the output sequenced slices to adispersed storage (DS) processing unit (e.g., that may have requestedslices and that may have provided a sequence seed and other information)for storage in at least one dispersed storage network (DSN) memory. Inan example, the processing module sends first buffered encoded dataslices and, at most, some second buffered encoded data slices of secondbuffered encoded data slices to the DSN memory for storage therein. Notethat the output sequenced slices may be communicated from the sourceuser device to the DS processing unit via one or more wireless modulesutilizing wireless signals.

FIG. 26 is another flowchart illustrating another example of decodingencoded data slices to produce data, which includes similar steps fromthe flowcharts of FIGS. 10, 12, and 22. The method begins with steps 234-252 of FIG. 10, step 602 of FIG. 22, steps 254-256 of FIG. 9, and step312 of FIG. 12. The method continues at step 730 where the processingmodule aggregates the plurality of data segments to produce a datastream or data object and determines second error coding dispersalstorage function parameters based on one or more of information in theretrieve data object message, a user device ID, a DS processing unit ID,a vault lookup, a predetermination, a command, and a message. Theprocessing module dispersed storage error and codes the data stream ordata object to produce a plurality of sets of re-encoded data slices inaccordance with the second error coding dispersal storage parameters.

The method continues at step 732 where the processing module sendsslices to the DSN memory for storage therein in accordance with theslice storage format. For example, the processing module sends theobtained encoded data slices to the DSN memory for storage therein whenthe processing module determines that the slice storage format includesstoring information in the format of the obtained encoded data slices(e.g., path A). In another example, the processing module sends theplurality of sets of encoded data slices to the DSN memory for storagetherein when the processing module determines that the slice storageformat includes storing information in the format of the plurality ofthe encoded data slices (e.g., path C). In another example, theprocessing module dispersed storage error encodes the plurality of datasegments to produce the plurality of sets of re-encoded data slices andsends the plurality of sets of re-encoded data slices to the DSN memoryfor storage therein when the processing module determines that the slicestorage format includes storing information in the format of re-encodeddata slices.

As may be used herein, the terms “substantially” and “approximately”provides an industry-accepted tolerance for its corresponding termand/or relativity between items. Such an industry-accepted toleranceranges from less than one percent to fifty percent and corresponds to,but is not limited to, component values, integrated circuit processvariations, temperature variations, rise and fall times, and/or thermalnoise. Such relativity between items ranges from a difference of a fewpercent to magnitude differences. As may also be used herein, theterm(s) “operably coupled to”, “coupled to”, and/or “coupling” includesdirect coupling between items and/or indirect coupling between items viaan intervening item (e.g., an item includes, but is not limited to, acomponent, an element, a circuit, and/or a module) where, for indirectcoupling, the intervening item does not modify the information of asignal but may adjust its current level, voltage level, and/or powerlevel. As may further be used herein, inferred coupling (i.e., where oneelement is coupled to another element by inference) includes direct andindirect coupling between two items in the same manner as “coupled to”.As may even further be used herein, the term “operable to” or “operablycoupled to” indicates that an item includes one or more of powerconnections, input(s), output(s), etc., to perform, when activated, oneor more its corresponding functions and may further include inferredcoupling to one or more other items. As may still further be usedherein, the term “associated with”, includes direct and/or indirectcoupling of separate items and/or one item being embedded within anotheritem. As may be used herein, the term “compares favorably”, indicatesthat a comparison between two or more items, signals, etc., provides adesired relationship. For example, when the desired relationship is thatsignal 1 has a greater magnitude than signal 2, a favorable comparisonmay be achieved when the magnitude of signal 1 is greater than that ofsignal 2 or when the magnitude of signal 2 is less than that of signal1.

The present invention has also been described above with the aid ofmethod steps illustrating the performance of specified functions andrelationships thereof. The boundaries and sequence of these functionalbuilding blocks and method steps have been arbitrarily defined hereinfor convenience of description. Alternate boundaries and sequences canbe defined so long as the specified functions and relationships areappropriately performed. Any such alternate boundaries or sequences arethus within the scope and spirit of the claimed invention.

The present invention has been described, at least in part, in terms ofone or more embodiments. An embodiment of the present invention is usedherein to illustrate the present invention, an aspect thereof, a featurethereof, a concept thereof, and/or an example thereof. A physicalembodiment of an apparatus, an article of manufacture, a machine, and/orof a process that embodies the present invention may include one or moreof the aspects, features, concepts, examples, etc. described withreference to one or more of the embodiments discussed herein.

The present invention has been described above with the aid offunctional building blocks illustrating the performance of certainsignificant functions. The boundaries of these functional buildingblocks have been arbitrarily defined for convenience of description.Alternate boundaries could be defined as long as the certain significantfunctions are appropriately performed. Similarly, flow diagram blocksmay also have been arbitrarily defined herein to illustrate certainsignificant functionality. To the extent used, the flow diagram blockboundaries and sequence could have been defined otherwise and stillperform the certain significant functionality. Such alternatedefinitions of both functional building blocks and flow diagram blocksand sequences are thus within the scope and spirit of the claimedinvention. One of average skill in the art will also recognize that thefunctional building blocks, and other illustrative blocks, modules andcomponents herein, can be implemented as illustrated or by discretecomponents, application specific integrated circuits, processorsexecuting appropriate software and the like or any combination thereof.

What is claimed is:
 1. A method for execution by a processing module ofa computing device, the method comprises: receiving a data objectretrieval message regarding receiving a transmission from a particularsource device; receiving, as the transmission, randomly ordered encodedslices from the particular source device; rearranging the randomlyordered encoded slices into first randomly ordered encoded data slicescorresponding to data and a set of second randomly ordered encoded dataslices corresponding to auxiliary data based on de-selectioninformation; ordering the second randomly ordered encoded data slicesinto a set of encoded data slices in accordance with auxiliary datade-sequencing information; decoding the set of encoded data slices inaccordance with operational parameters to produce auxiliary data; whenthe auxiliary data content corresponds to de-sequencing of the firstrandomly ordered encoded data slices, determining a pseudo randomde-sequencing order for the first randomly ordered encoded data slicesfrom the auxiliary data; ordering the first randomly ordered encodeddata slices based on the pseudo-random de-sequencing order to produce aplurality of sets of encoded data slices; dispersed storage errordecoding the plurality of sets of encoded data slices to produce aplurality of encrypted data segments; decrypting the plurality ofencrypted data segments to produce a plurality of data segments; andaggregating the plurality of data segments to produce the data.
 2. Themethod of claim 1, wherein the receiving the transmission comprises:receiving an inbound radio frequency (RF) signal; converting the inboundRF signal into a symbol stream in accordance with a wirelesscommunication protocol; and converting the symbol stream into therandomly ordered encoded slices in accordance with the wirelesscommunication protocol.
 3. The method of claim 1 further comprises:determining the de-selection information by: extracting informationregarding operational parameters of the transmission from the dataobject retrieval message; and determining de-selection information basedon the operational parameters.
 4. The method of claim 1, wherein thepseudo-random de-sequencing order comprises at least one of: ade-sequencing algorithm identifier (ID); a segment de-sequencingalgorithm ID; a slice de-sequencing algorithm ID; an algorithm seed; aseed generation algorithm ID; an encryption key; a hash algorithm ID;segment ordering information; and slice ordering information.
 5. Themethod of claim 1, wherein the auxiliary data, for determining thepseudo-random de-sequencing order, comprises at least one of: arequester identifier (ID); a vault lookup; a data object name; the data;received de-sequencing information; error coding dispersal storagefunction parameters; executing a de-sequencing algorithm utilizing analgorithm seed; a priority indicator; a security indicator; aperformance indicator; a list; a command; a predetermination; and amessage.
 6. The method of claim 1, wherein the decrypting the pluralityof encrypted data segments comprises at least one of: decrypting theplurality of encrypted data segments utilizing an all or nothingtransformation (AONT) to produce the plurality of data segments;decrypting the plurality of encrypted data segments utilizing a storeddecryption key to produce the plurality of data segments; decrypting theplurality of encrypted data segments utilizing a decryption keyassociated with at least one recipient to produce the plurality of datasegments; decrypting the plurality of encrypted data segments utilizingthe stored encryption key to produce a plurality of AONT encrypted datasegments and decrypting the plurality of AONT encrypted data segmentsutilizing the AONT to produce the plurality of data segments;de-obfuscating the plurality of encrypted data segments utilizing ade-obfuscating method to produce the plurality of data segments;selecting a decryption method based on a data type and decrypting theplurality of encrypted data segments utilizing the decryption method toproduce the plurality of data segments; and decrypting the plurality ofencrypted data segments utilizing a null decryption method to producethe plurality of data segments.
 7. The method of claim 1, wherein theaggregating the plurality of data segments comprises: ordering theplurality of data segments in accordance with a data segment order ofthe pseudo-random de-sequencing order to produce ordered data segments;and combining the ordered data segments to produce the data.
 8. Themethod of claim 1 further comprises at least one of: sending therandomly ordered encoded slices to a dispersed storage network (DSN)memory for storage therein; sending the plurality of encoded data slicesto the DSN memory for storage therein; and dispersed storage errorencoding the plurality of data segments to produce a new plurality ofsets of re-encoded data slices and sending the new plurality of sets ofre-encoded data slices to the DSN memory for storage therein.
 9. Themethod of claim 1, wherein aggregating the plurality of data segmentscomprises: ordering a plurality of randomly ordered data segments inaccordance with the pseudo-random de-sequencing order to produce theplurality of data segments; and aggregating the plurality of datasegments to produce the at least one data stream.
 10. The method ofclaim 1, wherein aggregating the plurality of data segments comprises:ordering the plurality of data segments into a first plurality of datasegment and a second plurality of data segments in accordance with thepseudo-random de-sequencing order; aggregating the first plurality ofdata segments to produce a first data stream of the data; andaggregating the second plurality of data segments to produce a seconddata stream of the data.
 11. A computer comprises: an interface; and aprocessing module operable to: receive a data object retrieval messageregarding receiving a transmission from a particular source device;receive, as the transmission, randomly ordered encoded slices from theparticular source device; rearrange the randomly ordered encoded slicesinto first randomly ordered encoded data slices corresponding to dataand second randomly ordered encoded data slices corresponding toauxiliary data based on de-selection information; order the secondrandomly ordered encoded data slices into a set of encoded data slicesin accordance with auxiliary data de-sequencing information; decode theset of encoded data slices in accordance with operational parameters toproduce auxiliary data; when the auxiliary data content corresponds tode-sequencing of the first randomly ordered encoded data slices,determine a pseudo random de-sequencing order for the first randomlyordered encoded data slices from the auxiliary data; order the firstrandomly ordered encoded data slices based on the pseudo-randomde-sequencing order to produce a plurality of sets of encoded dataslices; dispersed storage error decode the plurality of sets of encodeddata slices to produce a plurality of encrypted data segments; decryptthe plurality of encrypted data segments to produce a plurality of datasegments; and aggregate the plurality of data segments to produce thedata.
 12. The computer of claim 11, wherein the processing modulefurther functions to receive the transmission by: receiving an inboundradio frequency (RF) signal; converting the inbound RF signal into asymbol stream in accordance with a wireless communication protocol; andconverting the symbol stream into the randomly ordered encoded slices inaccordance with the wireless communication protocol.
 13. The computer ofclaim 11, wherein the processing module further functions to determinethe de-selection information by: extracting information regardingoperational parameters of the transmission from the data objectretrieval message; and determining de-selection information based on theoperational parameters.
 14. The computer of claim 11, wherein thepseudo-random de-sequencing order comprises at least one of: ade-sequencing algorithm identifier (ID); a segment de-sequencingalgorithm ID; a slice de-sequencing algorithm ID; an algorithm seed; aseed generation algorithm ID; an encryption key; a hash algorithm ID;segment ordering information; and slice ordering information.
 15. Thecomputer of claim 11, wherein the auxiliary data comprises at least oneof: a requester identifier (ID); a vault lookup; a data object name; thedata; received de-sequencing information; error coding dispersal storagefunction parameters; executing a de-sequencing algorithm utilizing analgorithm seed; a priority indicator; a security indicator; aperformance indicator; a list; a command; a predetermination; and amessage.
 16. The computer of claim 11, wherein the processing modulefurther functions to decrypt the plurality of encrypted data segments byat least one of: decrypting the plurality of encrypted data segmentsutilizing an all or nothing transformation (AONT) to produce theplurality of data segments; decrypting the plurality of encrypted datasegments utilizing a stored decryption key to produce the plurality ofdata segments; decrypting the plurality of encrypted data segmentsutilizing a decryption key associated with at least one recipient toproduce the plurality of data segments; decrypting the plurality ofencrypted data segments utilizing the stored encryption key to produce aplurality of AONT encrypted data segments and decrypting the pluralityof AONT encrypted data segments utilizing the AONT to produce theplurality of data segments; de-obfuscating the plurality of encrypteddata segments utilizing a de-obfuscating method to produce the pluralityof data segments; selecting a decryption method based on a data type anddecrypting the plurality of encrypted data segments utilizing thedecryption method to produce the plurality of data segments; anddecrypting the plurality of encrypted data segments utilizing a nulldecryption method to produce the plurality of data segments.
 17. Thecomputer of claim 11, wherein the processing module further functions toaggregate the plurality of data segments by: ordering the plurality ofdata segments in accordance with a data segment order of thepseudo-random de-sequencing order to produce ordered data segments; andcombining the ordered data segments to produce the data.
 18. Thecomputer of claim 11, wherein the processing module further functionsto: send, via the interface, the randomly ordered encoded slices to adispersed storage network (DSN) memory for storage therein; send, viathe interface, the plurality of encoded data slices to the DSN memoryfor storage therein; and dispersed storage error encode the plurality ofdata segments to produce a new plurality of sets of re-encoded dataslices and send, via the interface, the new plurality of sets ofre-encoded data slices to the DSN memory for storage therein.
 19. Thecomputer of claim 11, wherein the processing module further functions toaggregate the plurality of data segments by: ordering a plurality ofrandomly ordered data segments in accordance with the pseudo-randomde-sequencing order to produce the plurality of data segments; andaggregating the plurality of data segments to produce the at least onedata stream.
 20. The computer of claim 11, wherein the processing modulefurther functions to aggregate the plurality of data segments by:ordering the plurality of data segments into a first plurality of datasegment and a second plurality of data segments in accordance with thepseudo-random de-sequencing order; aggregating the first plurality ofdata segments to produce a first data stream of the data; andaggregating the second plurality of data segments to produce a seconddata stream of the data.